{"id":"W2997869660","doi":"10.1002/col.22471","title":"Evaluation of expanded gamut software solutions for spot color reproduction","year":2019,"lang":"en","type":"article","venue":"Color Research & Application","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Ryerson University","keywords":"Gamut; Color management; Computer graphics (images); Computer science; Software; Inkwell; RGB color model; Engineering drawing; Color space; Computer vision; Engineering; Operating system","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005936517,0.00009868912,0.0001558748,0.0001687142,0.0004326134,0.00004366385,0.0003270275,0.00004787438,0.0003020276],"category_scores_gemma":[0.0001931641,0.0001003415,0.00008703925,0.0008629513,0.0001483807,0.0002199488,0.000102784,0.0001484509,0.0001686916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001781436,"about_ca_system_score_gemma":0.0004648887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001284798,"about_ca_topic_score_gemma":0.00001967894,"domain_scores_codex":[0.9976386,0.0001449799,0.0003004207,0.0005797941,0.0009236872,0.0004125267],"domain_scores_gemma":[0.9963972,0.0002675532,0.0001618916,0.0007730616,0.002323549,0.00007676463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001365694,0.0008701753,0.00632599,0.00006449472,0.00007211763,1.749068e-8,0.0004996174,0.01134474,0.3444204,0.1359995,0.005763275,0.4945031],"study_design_scores_gemma":[0.003744341,0.0008629556,0.0399455,0.0000712557,0.0002671389,0.000001621408,0.003318999,0.4714239,0.1682094,0.2259805,0.08550865,0.0006657215],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.953639,0.00005353654,0.0370322,0.0008431925,0.00007875754,0.005665778,0.00006228568,0.0000450194,0.002580194],"genre_scores_gemma":[0.9901333,0.000003820447,0.001290665,0.000006608349,0.0002129377,0.007487899,0.0001892581,0.00001421716,0.0006612951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4938374,"threshold_uncertainty_score":0.4091809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1555796252450223,"score_gpt":0.4421782502271398,"score_spread":0.2865986249821175,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}